Biosensor systems provide an analysis of a biological fluid, such as whole blood, serum, plasma, urine, saliva, interstitial, or intracellular fluid. Typically, the systems include a measurement device that analyzes a sample in a test sensor. The sample usually is in liquid form and in addition to being a biological fluid, may be the derivative of a biological fluid, such as an extract, a dilution, a filtrate, or a reconstituted precipitate. The analysis performed by the biosensor system determines the presence and/or concentration of one or more analytes, such as alcohol, glucose, uric acid, lactate, cholesterol, bilirubin, free fatty acids, triglycerides, proteins, ketones, phenylalanine or enzymes, in the biological fluid. The analysis may be useful in the diagnosis and treatment of physiological abnormalities. For example, a diabetic individual may use a biosensor system to determine the glucose level in whole blood for adjustments to diet and/or medication.
Biosensor systems may be designed to analyze one or more analytes and may use different volumes of biological fluids. Some systems may analyze a single drop of whole blood including red blood cells, such as from 0.25-15 microliters (μL) in volume. Biosensor systems may be implemented using bench-top, portable, and like measurement devices. Portable measurement devices may be hand-held and allow for the identification and/or quantification of one or more analytes in a sample. Examples of portable measurement devices include the Ascensia® Breeze® and Elite® meters of Bayer HealthCare in Tarrytown, N.Y., while examples of bench-top measurement devices include the Electrochemical Workstation available from CH Instruments in Austin, Tex.
In electrochemical biosensor systems, the analyte concentration is determined from an electrical signal generated by an electrochemical oxidation/reduction or redox reaction of a measurable species when an excitation signal is applied to the sample. The measurable species may be ionized analyte or an ionized species responsive to the analyte, such as a mediator. The excitation signal may be a potential or current and may be constant, variable, or a combination thereof such as when an AC signal is applied with a DC signal offset. The excitation signal may be applied as a single pulse or in multiple pulses, sequences, or cycles.
Electrochemical biosensor systems usually include a measurement device having electrical contacts that connect with the electrical conductors of a test sensor. The electrical conductors may be made from conductive materials, such as solid metals, metal pastes, conductive carbon, conductive carbon pastes, conductive polymers, and the like. The electrical conductors typically connect to working, counter, reference, and/or other electrodes that extend into a sample reservoir. One or more electrical conductors also may extend into the sample reservoir to provide functionality not provided by the electrodes.
The test sensor may include reagents that react with the analyte in the sample. The reagents may include an ionizing agent for facilitating the redox reaction of the analyte, as well as mediators or other substances that assist in transferring electrons between the ionized analyte and the electrodes. The ionizing agent may be an analyte specific enzyme, such as glucose oxidase or glucose dehydrogenase, which catalyze the oxidation of glucose. The reagents may include a binder that holds the enzyme and mediator together. A binder is a polymeric material that is at least partially water-soluble and that provides physical support and containment to the reagents while having chemical compatibility with the reagents.
Mediators assist in the transfer of an electron from a first species to a second species. For example, a mediator may assist in the transfer of an electron from the redox reaction between the analyte and the oxidoreductase to or from the surface of the working electrode of the test sensor. A mediator also may assist in the transfer of an electron to or from the surface of the counter electrode to the sample. Mediators may be able to transfer one or more electrons during the conditions of the electrochemical reaction. Mediators may be organotransition metal complexes, such as ferrocyanide/ferricyanide; coordination compound metal complexes, such as ruthenium hexaamine; electroactive organic molecules, such as 3-phenylimino-3H-phenothiazines (PIPT) and 3-phenylimino-3H-phenoxazines (PIPO); and the like.
The test sensor may be placed in the measurement device and a sample introduced into the sample reservoir of the test sensor for analysis. A chemical redox reaction begins between the analyte, the ionizing agent, and any mediator to form an electrochemically measurable species. To analyze the sample, the measurement device applies the excitation signal to electrical contacts connected to the electrical conductors of the test sensor. The conductors convey the electrical signal to the electrodes that convey the excitation into the sample. The excitation signal causes an electrochemical redox reaction of the measurable species, which generates the analytic output signal. The electrical analytic output signal from the test sensor may be a current (as generated by amperometry or voltammetry), a potential (as generated by potentiometry/galvanometry), or an accumulated charge (as generated by coulometry). The measurement device determines the analyte concentration in response to the analytic output signal from the electrochemical redox reaction of the measurable species.
In amperometry, a potential or voltage is applied to the sample. The electrochemical redox reaction of the measurable species generates current in response to the potential. This current is measured at a fixed time at a substantially constant potential to quantify the analyte in the sample. Amperometry measures the rate at which the measurable species is electrochemical oxidized or reduced to determine the analyte concentration in the sample. Thus, amperometry does not measure the total amount of analyte in the sample, but determines the analyte concentration in the sample based on the electrochemical redox reaction rate of the analyte in response to time. Biosensor systems using amperometry are described in U.S. Pat. Nos. 5,620,579; 5,653,863; 6,153,069; and 6,413,411.
In coulometry, a potential is applied to the sample to exhaustively oxidize or reduce the measurable species within the sample. The applied potential generates a current that is integrated over the time of the electrochemical redox reaction to produce an electrical charge representing the analyte concentration. Coulometry generally attempts to capture the total amount of analyte within the sample, necessitating knowledge of sample volume to determine the analyte concentration in the sample. A biosensor system using coulometry for whole blood glucose measurement is described in U.S. Pat. No. 6,120,676.
In voltammetry, a varying potential is applied to the sample. The electrochemical redox reaction of the measurable species generates current in response to the applied potential. The current is measured as a function of applied potential to quantify the analyte in the sample. Voltammetry generally measures the rate at which the measurable species is oxidized or reduced to determine the analyte concentration in the sample. Thus, voltammetry does not measure the total amount of analyte in the sample, but determines the analyte concentration in the sample based on the electrochemical redox reaction rate of the analyte in response to potential.
In gated amperometry and gated voltammetry, pulsed excitations may be used as described in U.S. Pat. Pubs. 2008/0173552, filed Dec. 19, 2007, and 2008/0179197, filed Feb. 26, 2006, respectively.
The measurement performance of a biosensor system is defined in terms of accuracy, which reflects the combined effects of random and systematic error components. Systematic error, or trueness, is the difference between the average value determined from the biosensor system and one or more accepted reference values for the analyte concentration of the sample. Trueness may be expressed in terms of mean bias, with larger mean bias values representing lower trueness and thereby contributing to less accuracy. Precision is the closeness of agreement among multiple analyte readings in relation to a mean. One or more errors in the analysis contribute to the bias and/or imprecision of the analyte concentration determined by the biosensor system. A reduction in the analysis error of a biosensor system therefore leads to an increase in accuracy and thus an improvement in measurement performance.
Bias may be expressed in terms of “absolute bias” or “percent bias”. Absolute bias may be expressed in the units of the measurement, such as mg/dL, while percent bias may be expressed as a percentage of the absolute bias value over 100 mg/dL or the reference analyte concentration of the sample. For glucose concentrations less than 100 mg/dL, percent bias is defined as (the absolute bias over 100 mg/dL)*100. For glucose concentrations of 100 mg/dL and higher, percent bias is defined as the absolute bias over the reference analyte concentration*100. Accepted reference values for the analyte glucose in whole blood samples may be obtained with a reference instrument, such as the YSI 2300 STAT PLUS™ available from YSI Inc., Yellow Springs, Ohio. Other reference instruments and ways to determine percent bias may be used for other analytes.
The percent of analyses that fall within a “percent bias limit” of a selected percent bias boundary indicate the percent of the determined analyte concentrations that are close to a reference concentration. Thus, the limit defines how close the determined analyte concentrations are to the reference concentration. For instance, 95 out of 100 performed analysis (95%) falling within a ±10% percent bias limit is a more accurate result than 80 out of 100 performed analysis (80%) falling within a ±10% percent bias limit. Similarly, 95 out of 100 performed analyses falling within a ±5% percent bias limit is a more accurate result than 95 out of 100 performed analyses falling within a ±10% percent bias limit. Thus, an increase in the percentage of analyses falling within a selected percent bias limit or within a narrower percent bias limit represents an increase in the measurement performance of the biosensor system.
The mean may be determined for the percent biases determined from multiple analyses using test sensors to provide a “mean percent bias” for the multiple analyses. As a mean percent bias may be determined, a “percent bias standard deviation” also may be determined to describe how far the percent biases of multiple analyses are away from each other. Percent bias standard deviation may be considered an indicator of the precision of multiple analyses. Thus, a decrease in percent bias standard deviation represents an increase in the measurement performance of the biosensor system.
Increasing the measurement performance of the biosensor system by reducing errors from these or other sources means that more of the analyte concentrations determined by the biosensor system may be used for accurate therapy by the patient when blood glucose is being monitored, for example. Additionally, the need to discard test sensors and repeat the analysis by the patient also may be reduced.
A test case is a collection of multiple analyses (data population) arising under substantially the same testing conditions. For example, determined analyte concentration values have typically exhibited poorer measurement performance for user self-testing than for health care professional (“HCP”) testing and poorer measurement performance for HCP-testing than for controlled environment testing. This difference in measurement performance may be reflected in larger percent bias standard deviations for analyte concentrations determined through user self-testing than for analyte concentrations determined through HCP-testing or through controlled environment testing. A controlled environment is an environment where physical characteristics and environmental aspects of the sample may be controlled, preferably a laboratory setting. Thus, in a controlled environment, hematocrit concentrations can be fixed and actual sample temperatures can be known and compensated. In a HCP test case, operating condition errors may be reduced or eliminated. In a user self-testing test case, such as a clinical trial, the determined analyte concentrations likely will include error from all types of error sources.
The analytic output signal is used by the biosensor system to determine the analyte concentration of the sample. Biosensor systems may provide an analytic output signal during the analysis of the sample that includes one or multiple errors. These errors may be reflected in an abnormal output signal, such as when one or more portions or the entire output signal is non-responsive or improperly responsive to the analyte concentration of the sample. These errors may be from one or more error contributors, such as the physical characteristics of the sample, the environmental aspects of the sample, the operating conditions of the system, and the like. Physical characteristics of the sample include the hematocrit (red blood cell) concentration of whole blood, interfering substances, and the like. Interfering substances include ascorbic acid, uric acid, acetaminophen, and the like. Environmental aspects of the sample include temperature and the like. Operating conditions of the system include underfill conditions when the sample size is not large enough, slow-filling of the sample, intermittent electrical contact between the sample and one or more electrodes in the test sensor, degradation of the reagents that interact with the analyte, and the like. There may be other contributors or a combination of contributors that cause errors.
If a test sensor is underfilled with sample, the test sensor may provide an inaccurate analysis of the analyte in the sample. Biosensor systems may include an underfill detection system to prevent or screen out analyses associated with sample sizes that are of insufficient volume. Some underfill detection systems have one or more indicator electrodes that may be separate or part of the working, counter, or other electrodes used to determine the concentration of analyte in the sample. Other underfill detection systems have a third or indicator electrode in addition to the counter and working electrodes. Additional underfill detection systems have a sub-element in electrical communication with the counter electrode. Unlike working and counter electrodes, conductive sub-elements, trigger electrodes, and the like are not used to determine the analyte responsive signals generated by the biosensor system. Thus, they may be bare conductive traces, conductors with non-analyte specific reagents, such as mediators, and the like.
Typically, an electrical signal passes between the indicator electrode(s), between the third electrode and the counter electrode, or between the sub-element and the working electrode when a sample is present in the sample reservoir. The electrical signal indicates whether a sample is present and may indicate whether the sample partially or completely fills the sample reservoir. A biosensor using an underfill detection system with a third electrode is described in U.S. Pat. No. 5,582,697. A biosensor using an underfill detection system with a sub-element of the counter electrode is described in U.S. Pat. No. 6,531,040.
Other underfill methods may use an electrical property of the sample that changes with sample volume to determine underfill. For example, U.S. Pat. No. 6,797,150 discloses the use of capacitance to determine if a test sensor is too severely underfilled to analyze or if the test sensor is underfilled but analyzable if the determined concentration is adjusted. Unlike indicator electrode systems that depend only on the sample being conductive, electrical property based systems rely on an electrical property of the sample that changes with sample volume. In the '150 patent, if the test sensor is severely underfilled, the analysis is stopped. If the test sensor is underfilled, but analyzable with adjustment, the method applies the same analysis method used for a fully filled test sensor, but then adjusts the resulting determined analyte concentration with an offset value. Thus, this underfill analysis method can detect and analyze partially underfilled test sensors, but lacks the ability to correct the errors arising from test sensors needing additional sample to be properly analyzed.
While a conventional biosensor systems using an underfill detection system can analyze test sensors having some degree of underfill or reduce erroneous results due to an insufficient sample size by stopping the analysis or by instructing the user to add more sample; these underfill detection/analysis systems typically do not address analysis error arising from sample being added more than once to the test sensor, variances in sample fill rate, or variances in the sample addition profile. Sample addition profile errors arise when the sample does not evenly flow across the reagents.
There is an ongoing need for improved biosensor systems, especially those that may provide accurate and/or precise analyte concentration determination from underfilled test sensors that are subsequently fully filled for analysis. Such an improved biosensor system could compensate for error arising from refilled test sensors, variances in sample fill rates, and/or sample addition profiles. The systems, devices, and methods of the present invention overcome at least one of the disadvantages associated with conventional biosensor systems.